DALEC2a Model.pdf

The DALEC2a model is a carbon cycle model that simulates the dynamics of carbon pools and fluxes in terrestrial ecosystems. The model includes six carbon pools: labile carbon, foliar carbon, fine root carbon, above- and below-ground woody carbon, litter carbon, and soil organic carbon. The model also includes a water module that simulates plant-available water and evapotranspiration.

The model is driven by gross primary production (GPP), which is estimated using the Aggregated Canopy Model (ACM). The GPP is then allocated to the different carbon pools based on a set of parameters that control the allocation fractions. The model also includes a fire module that simulates the effects of fires on the carbon pools.

The model parameters are optimized using a Bayesian approach, which involves specifying prior ranges for the parameters and then updating these ranges based on observations of carbon fluxes and pools. The optimized parameters are then used to simulate the carbon cycle and evaluate the model's performance against observations.

The model is evaluated against a range of datasets, including FLUXCOM and FLUXSAT GPP estimates, and MODIS ET data. The evaluation is done for six subcontinental regions and the pantropical region, and the results show that the model is able to capture the inter-annual variability (IAV) of the carbon cycle.

The key equations of the model are:

Carbon pool dynamics: dC/dt = f(GPP) + (1 - φ) \ C
GPP estimation: GPP = ACM(GPP0, PAR, T, W)
Fire module: dC/dt = -FE - FM
Water module: dW/dt = P - ET - R

The model parameters are:

Allocation fractions: fauto, ffol, flab, fwoo, froo
Turnover rates: θwoo, θroo, θlit, θsom, θmin
Canopy parameters: donset, dfall, ceff, cLMA, cll, 2clr, cronset, crfall
Fire parameters: πfoliar, πbiomass, πSOM, r
Water parameters: ω, υ, α

The model state variables are:

Labile carbon: Clab
Foliar carbon: Cfol
Fine root carbon: Cfro
Above- and below-ground woody carbon: Cwoo
Litter carbon: Clit
Soil organic carbon: Csom
* Plant-available water: W

The model is able to capture the IAV of the carbon cycle, and the results show that the model is able to simulate the dynamics of the carbon pools and fluxes in response to changes in climate and disturbance regimes.